Competence

Competence Areas

Artificial Intelligence

In previous projects, we have incorporated rules systems as engines used by other servers in a backend. We have even integrated machine learning algorithms in the rules engine, either inserting rules obtained from machine learning algorithms like C4.5 or adding adaptive “black box” functions whose outcome will be handled by the rules.

Machine Learning and Statistical Learning

Our experience includes statistical tests on biological and telecom data, as well as more advanced clustering, classification and regression algorithms, including C4.5, COBWEB, K-means or Support Vector Machines (SVM).

Data Mining and Social Network Analysis

We have applied data mining and graph analysis on different sets of data, such as telecom usage data. Past work has included both traditional, offline data mining as well as automating data mining as part of a process; and the setup of a social network server.

Products and Tools

Our languages of choice are C, Erlang and Java. However, we acknowledge that our client may have its own software development tools, so we are prepared to work in a plethora of other languages like Matlab, Lisp, Smalltalk or even C++.

Our experience includes using the Pentaho Data Integration distribution tools to speed up the preparation of several Gbs of customer data, and extending Pentaho Data Mining with a distributed implementation of K-means.

Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.